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•The grain size decreased as rotational speed, milling time and balltopowderweightratio increased, the change of lattice strain was opposite.•The carbon and oxygen pollution levels ...introduced by stearic acid were higher than n-heptane and lower than ethanol.•Severe cold-welding resulted in the formation of Fe, Cr, Ni rich regions.•Concentration gradient sites were increased through refinement of particles and enrichment regions, accelerating dissolution and alloying.
Nine schemes were designed to study the effects of milling parameters (rotational speed, balltopowderweightratio, milling time) and process control agents (PCAs) on the synthesis of Al0.8Co0.5Cr1.5CuFeNi powders by mechanical alloying (MA). By using X-ray diffraction (XRD), the solid solutions formation during MA were studied, the grain size and lattice strain were calculated. The morphology, microstructure and composition of the powders were analyzed by scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS). The grain size decreased as rotational speed, milling time, balltopowderweightratio increased, the change of lattice strain was opposite. The carbon and oxygen pollution levels introduced by stearic acid were higher than those introduced by n-heptane and lower than those introduced by ethanol. The powders were hardly alloyed when stearic acid was added at initial stage, but could be effectively alloyed after pre-alloying. Cold-welding was effectively inhibited and particles were greatly refined when 1 wt% ethanol and stearic acid were added respectively. Solid solutions formation was affected by cold-welding and fracture. Severe cold-welding led to Fe, Cr, Ni rich regions formation. Refinement of particles and enrichment regions resulted in the increase of concentration gradient sites, accelerating dissolution and alloying.
In this study, the ball milling parameters (solids loading, binder and dispersant content, ball milling time) were optimized to control the granule size of the mold powder during spray drying and ...obtain good mechanical strength and metallurgical properties of the hollow granule mold powder. The effect of ball milling parameters on the granule size of mold powder was systematically investigated using computational fluid dynamics (CFD). A series of parameters, such as the temperature field, velocity field, granule size and trajectory were varied and the moisture content of the slurry in the spray drying tower was computed. To ensure that the granule size of the mold powder is controlled at 0.2–0.6 mm, the following optimum ball milling parameters were chosen based on the results of the numerical simulation: solid loading, 60 wt%; modified sodium carboxymethyl cellulose binder content, 1.0 wt%; sodium tripolyphosphate dispersant content, 0.5 wt%; ball-milling time, 60 min.
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•Mold powder slurry was prepared, and the viscosity was tested and analyzed.•A numerical simulation method for spray granulation was established.•The temperature and velocity field, moisture content, and diameter distribution were computed.•The optimum ball milling parameters were determined and applied in production.
Nano-structured duplex and ferritic stainless steel powders were prepared by high energy planetary milling of elemental Fe, Cr and Ni powders. Here, we have studied the effect of process control ...agent (PCA) such as stearic acid (SA), effect of ball to powder weight ratio (BPR 6:1and 12:1) and milling speed (64% and 75% critical speed) during planetary milling of elemental Fe–18Cr–13Ni (duplex) and Fe–17Cr–1Ni (ferritic) powders for 10h in a dual drive planetary mill (DDPM). We have found that all these milling parameters have great influence in tuning the final particle morphology, size and phase evolution during milling. It was found that addition of PCA, a BPR of 12:1 and 75% critical speed is more effective in reducing particle size and formation of duplex and ferritic stainless steel after 10h milling of elemental powder compositions than their counterparts. The particle size of duplex and ferritic stainless steel milled in the presence of SA for 10h is found to be 13 and 14μm, whereas the particle size is 20 and 16μm without SA respectively. The particle size of powder milled at 12:1 BPR is lower than powder milled at 6:1 BPR because of more impact energy induced by balls on powders and it is found to be 10 and 12μm respectively for duplex and ferrite in presence of SA. The median particle size of duplex and ferritic stainless steel milled at 75% critical speed is found to be 3.5 and 2.4μm respectively.
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•Duplex and ferritic stainless steel powders were prepared by DDPM for 10h.•Effects of PCA, BPR and milling speed were studied successfully.•Increase in BPR from 6:1 to 12:1 enhances phase transformation from α-Fe to γ-Fe.•PCA like SA can decrease the particle size but the shape of the powder is irregular.•Higher mill speed gives highly refined and spherical stainless steel powders.
In this study, mold powder slurries with high solid loading and low viscosity were prepared during the ball-milling process for improving the homogeneity and mechanical properties of granules after ...spray-drying. The effect of ball-milling parameters, such as solid loading, binder/dispersant content, and ball-milling time, on the flowability, dispersibility, stability, and rheological behavior of mold powder slurries was systematically investigated by rheology observation and sedimentation tests. As these parameters varied, the slurry exhibited the shear-thinning behavior of a non-Newtonian fluid with a shear rate range of 0–50 s−1, which was adequately described by the Herschel-Bulkley model. The optimal parameters that optimized the flowability, dispersibility, and stability of the slurry, along with its rheological behavior, were chosen as follows: solid loading, 60 wt%; modified sodium carboxymethyl cellulose binder content, 1.0 wt%; sodium tripolyphosphate dispersant content, 0.5 wt%; ball-milling time, 60 min.
The concept of steady state milling time was examined for ball milling of aluminum powder. Four different set-ups of balls were used while the mill speed and charge ratio were kept fixed. Different ...criteria (morphology of particles, average particle size, deviation from the average particle size, lattice imperfections and change in crystallographic orientation) were used to study structural evolution of the milled particles and to compare the steady state time for the different milling conditions. Results showed that different criteria may not determine the same steady state time, however, all criteria were consistent in comparing efficiency of the different milling conditions. Moreover, it was found that at a given mill speed and ball to powder ratio (i.e. at a given consumed energy), a change in balls size and filling ratio of vials can improve milling efficiency. Finally, the effect of energy of each impact and the collective energy of all impacts were discussed.
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•At a fixed ball to powder ratio, a change in balls size can significantly change the steady state milling time.•High energy impacts are preferred over a high number of low energy impacts.•Flattening of the particles is a result of accumulation of impacts in a particular direction.
The cutting parameters in the part machining process have a great impact on the energy efficiency and economy of the machining system. The cutting parameters in traditional machining are often ...selected according to the operator's experience, which lack attentions to energy saving and economy. Therefore, a milling process parameter optimization method based on deep reinforcement learning (DRL) is proposed in this paper. Taking the machining cost composed of cutting energy efficiency and machining time cost as the optimization goal, the spindle speed and feed speed under the combination of different cutting depth and cutting width parameters are optimized. Firstly, the machine tool energy consumption model is established by back propagation neural network (BPNN) regression method to realize the continuity of machine tool energy consumption state prediction, and the processing cost model is established as the optimization objective function. Then, the process parameter optimization problem is formally expressed as a Markov decision process (MDP), and the corresponding states, actions, reward functions and constraints are defined. Finally, combined with the machine tool power consumption model and machining cost model, the simulation environment is established, and the BP-TD3 method is proposed to solve the Markov decision problem of milling parameter optimization. Taking the machining center as an example, the aluminum alloy workpiece is milled. Compared with the classical optimization algorithm, the proposed method can save 95 % optimization calculation time, and ensure that the average processing cost after optimization is close to the minimum processing cost obtained by the classical optimization algorithm.
This research investigates how different ball milling conditions influence the microstructure and mechanical properties of carbon nanotube/aluminum alloys. The study examines varying rotation speeds, ...specifically 200, 300, and 400 rpm. The results highlight the significant impact of milling conditions on grain size and mechanical properties. Notably, milling at 300 rpm /4 h and at 400 rpm/2 h led to higher tensile strength but lower uniform elongation compared to milling at 200 rpm/6 h. The alloy milled at 300 rpm/4 h displayed a refined microstructure, increased density, and the strongest fiber texture along the (111) direction. At 300 rpm/4 h, the presence of a moderate grain size promoted ductility, resulting in the highest uniform elongation (∼9.1%) combined with high strength (∼515 MPa). This in turn means an increase in UTS by 23% and uniform elongation by 3.4% compared to 400 rpm/2 h. The formation of MgAl2O4 at higher rotational speeds positively influences the CNT–Al interface by alleviating the adverse effects of interfacial oxide (Al2O3), resulting in improved bonding and, consequently, enhanced tensile properties. This study provides valuable insights into the effects of ball milling on the microstructure and mechanical properties of metals and alloys, contributing to the optimization of milling conditions to achieve desired material characteristics.
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•Ball milling conditions significantly impact microstructure and properties.•300 rpm/4 h milling yields high strength but lower elongation.•Moderate grain size promotes uniform deformation and high elongation.•Optimization of milling parameters enhances composite understanding.
This study evaluates the influence of milling parameters on the milling process and microstructural changes in 7075-T6 aluminum alloy using experimental and simulation methods. Key findings include a ...direct correlation between milling parameters and higher chip temperatures, particularly influenced by milling speed which at its third level can cause temperature elevations up to 36 °C, ordered by impact as ap > f > v.Increasing milling depth markedly affects grain recrystallization, especially near the tool's trailing face (P3), leading to a 45.8% reduction in dynamic recrystallization, whereas lower depths expedite this process. Additionally, grain size and number at the leading face (P1) are also depth-dependent, with larger grains diminishing in volume yet increasing in quantity as depth increases. Enhanced milling speeds up to 500 mm/min significantly refine grains to near 1 μm at P1, with an 80.7% rise in recrystallization numbers, while at P3, grain size initially contracts then enlarges at 416 mm/min. Feed rate primarily impacts the quantity of recrystallized grains at the tool tip (P2), with a notable 60.4% increment and a swift transition from larger to smaller grains. Both P1 and P2 experience about a 20% reduction in grain growth due to feed rate, with more pronounced effects at P1 and the fragmentation of larger boundary grains into smaller, irregular shapes.
•7075 aluminum alloy machining microstructure evolution law was explored.•The influence of cutting parameters on microstructure evolution was explored.•The microstructure evolution of different deformation zones was compared.
In metal cutting, the cutting force is the key factor affecting the machined surface, and is also important in determining reasonable cutting parameters. The research and construction of cutting ...force prediction models therefore has a great practical value. The accuracy of cutting force prediction largely depends on the cutting force coefficients of the material. In the average cutting force model, cutting force coefficients are considered to be constant. This study makes use of experiments to investigate the cutting force coefficients in the average cutting force model, with a view to accurately identifying cutting force coefficients and verifying that they are related only to the tool–workpiece material couple and the tool geometrical parameters, and are not affected by milling parameters. To this end, the paper first examines the theory behind identifying cutting force coefficients in the average cutting force model. Based on this theory, a series of slot-milling experiments are performed to measure the milling forces, fixing spindle speeds and radial/axial depths of cutting, and linearly varying the feed per tooth. The tangential milling force coefficient and the radial milling force coefficient are then calculated by linearly fitting the experimental data. The obtained results show that altering the milling parameters does not change the milling force coefficients for the selected tool/workpiece material combination.
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•The cutting force coefficients in the average cutting force model are constants.•A series of tests are performed to investigate the cutting force coefficients.•The cutting force coefficients are not affected by milling parameters.•The cutting force coefficients depend on the tool–workpiece material combination.•This finding offers a theoretical basis for studying milling chatter.
In the field of mechanical manufacturing, CNC machining technology plays an important role in improving the precision and efficiency of part processing. However, how to further improve the effect of ...NC machining by optimizing milling parameters is still a key problem. The aim of this study is to optimize CNC milling parameters through systematic research and experiments to improve the machining efficiency and quality of mechanical parts. By adjusting key parameters such as tool speed, feed speed, and removal rate cutting depth, the influence of these parameters on the milling process was systematically studied using advanced CNC machining equipment. Through the collection and analysis of experimental data, the mathematical model is established, and the optimization algorithm is applied to find the best combination of milling parameters. The experimental results show that under the optimal combination of parameters, the surface quality of parts can be significantly improved, the machining time can be reduced, and the tool wear can be reduced. This research successfully realizes the optimization of milling parameters of mechanical parts by CNC machining technology and provides an effective solution for improving machining efficiency and reducing costs. This not only has guiding significance for the application of CNC machining technology but also has important promotion value in actual production.
